Lane Model Validation: Ground Truth Generation and Lane Model Evaluation

Detalhes bibliográficos
Autor(a) principal: Baur, Alexandra
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/137126
Resumo: Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
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spelling Lane Model Validation: Ground Truth Generation and Lane Model EvaluationLane Model ValidationLane Detection EvaluationGround Truth GenerationInternship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsGenerating ground truth data for training models that are supposed to replace humans for certain tasks, such as in the field of autonomous driving is a big issue for many researchers all over the world. Over different problems in this field there a various approaches to deal with a ground truth generation that does not rely on time consuming and expensive labelling, yet being able to evaluate the performance of models not only qualitatively. Most of the quantitative approaches are using camera images and some are considering GPS data as well. In this report, the data used is the output of a line detection algorithm including positional information per frame and GPS data. Based on the localization of both vehicle and lines, the model can be evaluated by its ability to detect road geometries. The approach results in an estimation of road boundaries that is based on real road markings, but depends on a good parameter choice and input quality. Nevertheless, it is a rather fast and inexpensive way to generate a ground truth that can be compared to the model output in order to evaluate its performance on detecting a valid road geometry.Pinheiro, Flávio Luís PortasRUNBaur, Alexandra2022-04-29T12:55:23Z2022-04-112022-04-11T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/137126TID:202993787enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:14:49Zoai:run.unl.pt:10362/137126Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:48:48.412565Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Lane Model Validation: Ground Truth Generation and Lane Model Evaluation
title Lane Model Validation: Ground Truth Generation and Lane Model Evaluation
spellingShingle Lane Model Validation: Ground Truth Generation and Lane Model Evaluation
Baur, Alexandra
Lane Model Validation
Lane Detection Evaluation
Ground Truth Generation
title_short Lane Model Validation: Ground Truth Generation and Lane Model Evaluation
title_full Lane Model Validation: Ground Truth Generation and Lane Model Evaluation
title_fullStr Lane Model Validation: Ground Truth Generation and Lane Model Evaluation
title_full_unstemmed Lane Model Validation: Ground Truth Generation and Lane Model Evaluation
title_sort Lane Model Validation: Ground Truth Generation and Lane Model Evaluation
author Baur, Alexandra
author_facet Baur, Alexandra
author_role author
dc.contributor.none.fl_str_mv Pinheiro, Flávio Luís Portas
RUN
dc.contributor.author.fl_str_mv Baur, Alexandra
dc.subject.por.fl_str_mv Lane Model Validation
Lane Detection Evaluation
Ground Truth Generation
topic Lane Model Validation
Lane Detection Evaluation
Ground Truth Generation
description Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
publishDate 2022
dc.date.none.fl_str_mv 2022-04-29T12:55:23Z
2022-04-11
2022-04-11T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/137126
TID:202993787
url http://hdl.handle.net/10362/137126
identifier_str_mv TID:202993787
dc.language.iso.fl_str_mv eng
language eng
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dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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